ReviewJournal of echocardiography2023
Revolution of echocardiographic reporting: the new era of artificial intelligence and natural language processing.
Review in Journal of echocardiography, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 24 citations in OpenAlex.
- Ultrasound in cardiovascular care: a perspective on preventive, diagnostic, and monitoring applications.Frontiers in cardiovascular medicine · 2026Article
- Artificial intelligence in echocardiography: current applications and future perspectives.Journal of echocardiography · 2025Review
- Inter-machine harmonization of multicenter echocardiographic images for improvement of left ventricular ejection fraction prediction model.Scientific reports · 2025Article
- Editorial for the Special Issue "Novel Echocardiographic Techniques for the Assessment of Cardiovascular Disease".Medicina (Kaunas, Lithuania) · 2025Article
- Transforming Echocardiography: The Role of Artificial Intelligence in Enhancing Diagnostic Accuracy and Accessibility.Internal medicine (Tokyo, Japan) · 2025Review
- Harnessing the Power of ChatGPT in Cardiovascular Medicine: Innovations, Challenges, and Future Directions.Journal of clinical medicine · 2024Review
- Multicenter validation study for automated left ventricular ejection fraction assessment using a handheld ultrasound with artificial intelligence.Scientific reports · 2024Article
- Chest ultrasound for lung cancer: present and future.Journal of medical ultrasonics (2001) · 2024Article
- Exploring the Role of ChatGPT in Cardiology: A Systematic Review of the Current Literature.Cureus · 2024Review
- Accuracy of ChatGPT on Medical Questions in the National Medical Licensing Examination in Japan: Evaluation Study.JMIR formative research · 2023Article
- Embracing AI: The Imperative Tool for Echo Labs to Stay Ahead of the Curve.Diagnostics (Basel, Switzerland) · 2023Article
- Echocardiographic reporting, artificial intelligence and natural language processing: correspondence.Journal of echocardiography · 2023Article
- Trustworthy AI in Telehealth: Navigating Challenges, Ethical Considerations, and Future Opportunities for Equitable Healthcare Delivery.Healthcare technology lettersReview
- Artificial Intelligence and Echocardiography: From Literacy to Leadership, Redefining Roles, Responsibilities, and Sustainability in the Artificial Intelligence-driven Echocardiography Era.Journal of cardiovascular echographyReview
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has been making a significant impact on cardiovascular imaging, transforming everything from data capture to report generation. In the field of echocardiography, AI offers the potential to enhance accuracy, speed up reporting, and reduce the workload of physicians. This is an advantage because, compared to computed tomography and magnetic resonance imaging, echocardiograms tend to exhibit higher observer variability in interpretation. This review takes a comprehensive viewpoint at AI-based reporting systems and their application in echocardiography, emphasizing the need for automated diagnoses. The integration of natural language processing (NLP) technologies, including ChatGPT, could provide revolutionary advancements. One of the exciting prospects of AI integration is its potential to accelerate reporting, thereby improving patient outcomes and access to treatment, while also mitigating physician burnout. However, AI introduces new challenges like ensuring data quality, managing potential over-reliance on AI, addressing legal and ethical concerns, and balancing significant costs against benefits. As we navigate these complexities, it's important for cardiologists to stay updated with AI advancements and learn to utilize them effectively. AI has the potential to be integrated into daily clinical practice, becoming a valuable tool for healthcare professionals dealing with heart diseases, provided it's approached with careful consideration.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.